Due to the rapid spread of COVID-19, multiple nations have suffered large infection rates, many of which have been recorded, along with specific information on when the cases were first observed, in addition to status on the outcomes of each patient. This data is what we will be basing our research on.
country with most cases country with least cases 3 more points of interest Notable points of interest in the dataset are that ‘r’ contains the most confirmed cases in the world, with ‘r’ containing the least.
A table was included because it was the most clear way to display specific numeric values, and in this case, was used to show the twenty countries with the most recorded deaths. This table reveals how the US leads the world in number of deaths by a large margin. By listing out the results by number of deaths, we can more easily see the countries that have been most affected by COVID-19, and additional information for those countries
## Selecting by Total Deaths
| Country | Confirmed Cases | Recovered Cases | Total Deaths |
|---|---|---|---|
| US | 31464810 | 3460788 | 1684929 |
| Italy | 8057805 | 2211736 | 1025162 |
| Spain | 7952504 | 3282730 | 833391 |
| China | 7442665 | 5428530 | 305817 |
| Germany | 6039054 | 3480471 | 183272 |
| France | 5680108 | 1471182 | 737512 |
| United Kingdom | 4984308 | 25348 | 735428 |
| Iran | 3687232 | 2330420 | 232795 |
| Turkey | 3325094 | 1031075 | 82193 |
| Brazil | 2166180 | 844888 | 141527 |
| Canada | 1549581 | 544413 | 78829 |
| Belgium | 1538687 | 339568 | 208917 |
| Netherlands | 1321384 | 8894 | 147309 |
| Switzerland | 1193056 | 677483 | 54760 |
| India | 905084 | 215556 | 29599 |
| Portugal | 814581 | 36565 | 28458 |
| Sweden | 633667 | 45730 | 66285 |
| Ecuador | 604798 | 51466 | 26838 |
| Ireland | 586373 | 236833 | 29121 |
| Mexico | 477103 | 240781 | 42669 |
This map displays the number of cases per a country. We included this chart because it very clearly displays how the number of COVID19 cases is dispersed throughout the world. As seen below, this graphic reveals that the number of cases in the U.S. far out weighs the number of cases elsewhere.
## Reading layer `countries' from data source `C:\Users\hubhu\Documents\A1 Q3 2019\INFO 201\code\final-project-jzli23\data\countries.geojson' using driver `GeoJSON'
## Simple feature collection with 255 features and 3 fields
## geometry type: MULTIPOLYGON
## dimension: XY
## bbox: xmin: -180 ymin: -90 xmax: 180 ymax: 83.6341
## geographic CRS: WGS 84
## Warning: Column `Country`/`ADMIN` joining character vector and factor, coercing
## into character vector
## Reading layer `countries' from data source `C:\Users\hubhu\Documents\A1 Q3 2019\INFO 201\code\final-project-jzli23\data\countries.geojson' using driver `GeoJSON'
## Simple feature collection with 255 features and 3 fields
## geometry type: MULTIPOLYGON
## dimension: XY
## bbox: xmin: -180 ymin: -90 xmax: 180 ymax: 83.6341
## geographic CRS: WGS 84
## Warning: Column `Country`/`ADMIN` joining character vector and factor, coercing
## into character vector